Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "84" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 44 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 42 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2459859 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | - | - | 6.726509 | 22.887670 | 0.219486 | 12.650522 | 0.132803 | 2.586600 | -0.437732 | 3.282905 | 0.7296 | 0.0422 | 0.6227 | nan | nan |
| 2459858 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 7.095084 | 24.511368 | 0.256342 | 13.027577 | 0.262563 | 2.657321 | -0.484317 | 5.994692 | 0.7380 | 0.0394 | 0.6225 | 2.695855 | 1.124979 |
| 2459857 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 11.875286 | 5.635379 | 4.116809 | 6.799146 | 3.658522 | 5.116851 | 7.436837 | 19.715645 | 0.0270 | 0.0221 | 0.0017 | nan | nan |
| 2459856 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 10.598259 | 35.670307 | -0.325769 | 32.461292 | -1.162060 | 11.572470 | -0.680063 | 8.067794 | 0.7292 | 0.0410 | 0.6133 | 2.739763 | 1.150857 |
| 2459855 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 11.235653 | 37.310551 | -0.474298 | 34.021081 | -1.046192 | 4.116158 | -0.745156 | 3.553426 | 0.7119 | 0.0412 | 0.5917 | 2.653930 | 1.128398 |
| 2459854 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 11.487937 | 36.725546 | -0.367820 | 26.211749 | -0.670841 | 4.222431 | 0.952958 | 8.191281 | 0.7244 | 0.0445 | 0.6085 | 2.583658 | 1.128660 |
| 2459853 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 9.265092 | 30.746781 | -0.202615 | 35.725930 | -0.923370 | 10.407340 | -0.578637 | 8.488363 | 0.7531 | 0.0443 | 0.6341 | 3.165093 | 1.134478 |
| 2459852 | digital_ok | 100.00% | 29.19% | 100.00% | 0.00% | 100.00% | 0.00% | 6.708118 | 21.962876 | -0.351655 | 37.309660 | -1.388262 | 19.284236 | -1.024322 | 16.481224 | 0.6194 | 0.0488 | 0.5047 | 3.746401 | 1.140947 |
| 2459851 | digital_ok | 100.00% | 0.00% | 89.69% | 0.00% | 100.00% | 0.00% | 7.927263 | 34.173164 | -0.082256 | 39.650657 | -0.342417 | 42.212423 | -0.036486 | 24.089677 | 0.7751 | 0.1061 | 0.5909 | 3.686608 | 1.217326 |
| 2459850 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 8.662920 | 34.102687 | -0.232493 | 33.284430 | -0.923094 | 18.924066 | -0.508955 | 20.243970 | 0.7526 | 0.0684 | 0.5958 | 2.950553 | 1.126699 |
| 2459849 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 10.678095 | 35.441107 | 0.607314 | 65.557136 | -1.176766 | 12.391025 | -0.315954 | 11.415686 | 0.7533 | 0.0506 | 0.5994 | 4.089584 | 1.184771 |
| 2459848 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 9.821175 | 31.837263 | 0.490429 | 43.457779 | -0.603990 | 21.245589 | -0.573392 | 7.830393 | 0.7302 | 0.0467 | 0.5894 | 3.503843 | 1.191158 |
| 2459847 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 10.667243 | 34.542751 | 0.446831 | 40.968647 | -0.302902 | 27.684758 | -0.834645 | 3.988725 | 0.7415 | 0.0361 | 0.6025 | 3.550781 | 1.148016 |
| 2459846 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 10.730701 | 46.128872 | 0.273712 | 45.387903 | -1.183988 | 20.727381 | -0.659062 | 7.113025 | 0.8577 | 0.0394 | 0.7087 | 3.568027 | 1.186962 |
| 2459845 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
| 2459844 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459843 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | 0.000000 | 0.000000 |
| 2459842 | digital_ok | 100.00% | 0.00% | 100.00% | 0.00% | 100.00% | 0.00% | 5.706930 | 22.293601 | 0.521598 | 11.182460 | 0.258205 | -0.819242 | -0.068658 | 2.542763 | 0.7568 | 0.1443 | 0.5844 | 7.647388 | 1.285886 |
| 2459841 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459840 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 55.814014 | 53.118482 | 7.711764 | 6.612724 | 2.632276 | 6.341523 | 10.191682 | 16.220769 | 0.0270 | 0.0222 | 0.0019 | nan | nan |
| 2459839 | digital_ok | 100.00% | - | - | - | - | - | 14.126366 | 13.603923 | 18.286684 | 16.163685 | 1.317266 | 3.166992 | 14.314067 | 21.449425 | nan | nan | nan | nan | nan |
| 2459838 | digital_ok | 100.00% | 0.00% | 99.39% | 0.00% | 100.00% | 0.00% | 10.467097 | 34.214395 | 0.694339 | 27.491922 | -1.895993 | 28.481339 | -0.611271 | 4.304529 | 0.7628 | 0.1723 | 0.6180 | 5.131002 | 1.391738 |
| 2459836 | digital_ok | - | 100.00% | 100.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.0347 | 0.0312 | 0.0023 | nan | nan |
| 2459835 | digital_ok | 0.00% | 100.00% | 100.00% | 0.00% | - | - | 0.181494 | -0.384611 | -0.846630 | 2.163925 | 1.055729 | -0.539755 | 0.927359 | 1.331589 | 0.0335 | 0.0320 | 0.0008 | nan | nan |
| 2459833 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | 3.805989 | 3.473621 | 4.077631 | 3.092627 | 2.656595 | 1.367186 | 6.495203 | 9.032488 | 0.0273 | 0.0257 | 0.0009 | nan | nan |
| 2459832 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 14.959624 | 16.437997 | 0.972498 | -0.062260 | -1.461714 | 3.593770 | 0.099741 | 2.463329 | 0.8176 | 0.5806 | 0.5398 | 3.176855 | 3.749692 |
| 2459831 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459830 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 13.952381 | 16.537365 | 1.813190 | 0.712513 | -0.370727 | 0.131610 | -0.057114 | -0.489891 | 0.8195 | 0.6002 | 0.5103 | 4.645964 | 5.457097 |
| 2459829 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 17.762379 | 20.770730 | 1.729179 | 0.996610 | 11.286684 | 0.800048 | 0.273621 | 0.794915 | 0.7700 | 0.7024 | 0.3744 | 7.016006 | 8.908049 |
| 2459828 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 11.516768 | 13.037399 | 0.823678 | 1.044612 | -0.153946 | 0.709234 | 0.125889 | -0.249453 | 0.8189 | 0.6039 | 0.4978 | 5.238958 | 6.936172 |
| 2459827 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 14.380185 | 15.600494 | 2.043653 | 1.431114 | -1.007270 | 0.722977 | -0.688205 | -1.332677 | 0.7792 | 0.7091 | 0.3789 | 14.017173 | 13.947425 |
| 2459826 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 10.629806 | 11.535787 | 1.963192 | 1.034986 | 0.366545 | 1.216126 | -0.486848 | 0.615419 | 0.8157 | 0.6131 | 0.4874 | 8.223320 | 9.309866 |
| 2459825 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 11.647380 | 12.030065 | 0.654191 | 0.638365 | -0.359646 | 0.018064 | -0.508247 | -0.866460 | 0.8199 | 0.6413 | 0.4696 | 6.989423 | 9.069015 |
| 2459824 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 12.150956 | 12.882267 | -0.030395 | 0.826070 | -0.828183 | -0.426194 | -0.347431 | -0.608988 | 0.7482 | 0.7714 | 0.3308 | 7.244478 | 7.262122 |
| 2459823 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 7.231308 | 8.839119 | 0.659478 | 0.981154 | 0.123828 | -0.535560 | -0.388015 | 0.350581 | 0.7866 | 0.6925 | 0.4208 | 202.509415 | 110.692068 |
| 2459822 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 10.504014 | 11.856045 | 0.864122 | 1.138214 | -0.241103 | -0.080198 | -0.563475 | -0.982278 | 0.8166 | 0.6542 | 0.4726 | 4.916173 | 5.105727 |
| 2459821 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 9.781317 | 11.608880 | 0.013626 | 0.910668 | 8.287362 | -0.456988 | 86.636426 | -0.752886 | 0.8204 | 0.6800 | 0.4568 | 4.397673 | 4.491993 |
| 2459820 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 13.221487 | 15.032129 | 0.359319 | 1.272964 | 9.637161 | 2.454155 | 38.665378 | 1.429280 | 0.7899 | 0.7271 | 0.3827 | 5.074244 | 5.879466 |
| 2459817 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 9.128897 | 9.503435 | 0.600020 | 1.143740 | -0.430413 | 0.403788 | 0.841596 | 0.390744 | 0.8294 | 0.7120 | 0.4548 | 3.283303 | 3.389571 |
| 2459816 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 11.016819 | 10.402937 | 0.901336 | 1.113647 | -0.038009 | 1.124988 | -0.493928 | 3.231141 | 0.8558 | 0.6355 | 0.5548 | 4.033310 | 4.099301 |
| 2459815 | digital_ok | 100.00% | 0.00% | 0.00% | 0.00% | 100.00% | 0.00% | 8.321450 | 9.109864 | -0.076577 | 0.978449 | -0.658873 | 0.913709 | -0.558162 | 2.278572 | 0.8316 | 0.7281 | 0.4578 | 4.648080 | 4.731117 |
| 2459814 | digital_ok | 0.00% | - | - | - | - | - | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459813 | digital_ok | 100.00% | 100.00% | 100.00% | 0.00% | 100.00% | 0.00% | 16.867172 | 19.316557 | -0.180092 | 0.772046 | -1.082286 | 1.887260 | 0.393953 | 0.446668 | 0.0536 | 0.0730 | 0.0072 | 0.000000 | 0.000000 |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 22.887670 | 6.726509 | 22.887670 | 0.219486 | 12.650522 | 0.132803 | 2.586600 | -0.437732 | 3.282905 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 24.511368 | 24.511368 | 7.095084 | 13.027577 | 0.256342 | 2.657321 | 0.262563 | 5.994692 | -0.484317 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Temporal Discontinuties | 19.715645 | 5.635379 | 11.875286 | 6.799146 | 4.116809 | 5.116851 | 3.658522 | 19.715645 | 7.436837 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 35.670307 | 10.598259 | 35.670307 | -0.325769 | 32.461292 | -1.162060 | 11.572470 | -0.680063 | 8.067794 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 37.310551 | 37.310551 | 11.235653 | 34.021081 | -0.474298 | 4.116158 | -1.046192 | 3.553426 | -0.745156 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 36.725546 | 36.725546 | 11.487937 | 26.211749 | -0.367820 | 4.222431 | -0.670841 | 8.191281 | 0.952958 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Power | 35.725930 | 30.746781 | 9.265092 | 35.725930 | -0.202615 | 10.407340 | -0.923370 | 8.488363 | -0.578637 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Power | 37.309660 | 6.708118 | 21.962876 | -0.351655 | 37.309660 | -1.388262 | 19.284236 | -1.024322 | 16.481224 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Temporal Variability | 42.212423 | 7.927263 | 34.173164 | -0.082256 | 39.650657 | -0.342417 | 42.212423 | -0.036486 | 24.089677 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 34.102687 | 8.662920 | 34.102687 | -0.232493 | 33.284430 | -0.923094 | 18.924066 | -0.508955 | 20.243970 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Power | 65.557136 | 10.678095 | 35.441107 | 0.607314 | 65.557136 | -1.176766 | 12.391025 | -0.315954 | 11.415686 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Power | 43.457779 | 31.837263 | 9.821175 | 43.457779 | 0.490429 | 21.245589 | -0.603990 | 7.830393 | -0.573392 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Power | 40.968647 | 34.542751 | 10.667243 | 40.968647 | 0.446831 | 27.684758 | -0.302902 | 3.988725 | -0.834645 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 46.128872 | 10.730701 | 46.128872 | 0.273712 | 45.387903 | -1.183988 | 20.727381 | -0.659062 | 7.113025 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 22.293601 | 5.706930 | 22.293601 | 0.521598 | 11.182460 | 0.258205 | -0.819242 | -0.068658 | 2.542763 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | ee Shape | 55.814014 | 55.814014 | 53.118482 | 7.711764 | 6.612724 | 2.632276 | 6.341523 | 10.191682 | 16.220769 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Temporal Discontinuties | 21.449425 | 13.603923 | 14.126366 | 16.163685 | 18.286684 | 3.166992 | 1.317266 | 21.449425 | 14.314067 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 34.214395 | 34.214395 | 10.467097 | 27.491922 | 0.694339 | 28.481339 | -1.895993 | 4.304529 | -0.611271 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Power | 2.163925 | -0.384611 | 0.181494 | 2.163925 | -0.846630 | -0.539755 | 1.055729 | 1.331589 | 0.927359 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Temporal Discontinuties | 9.032488 | 3.473621 | 3.805989 | 3.092627 | 4.077631 | 1.367186 | 2.656595 | 9.032488 | 6.495203 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 16.437997 | 14.959624 | 16.437997 | 0.972498 | -0.062260 | -1.461714 | 3.593770 | 0.099741 | 2.463329 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 16.537365 | 13.952381 | 16.537365 | 1.813190 | 0.712513 | -0.370727 | 0.131610 | -0.057114 | -0.489891 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 20.770730 | 20.770730 | 17.762379 | 0.996610 | 1.729179 | 0.800048 | 11.286684 | 0.794915 | 0.273621 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 13.037399 | 13.037399 | 11.516768 | 1.044612 | 0.823678 | 0.709234 | -0.153946 | -0.249453 | 0.125889 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 15.600494 | 14.380185 | 15.600494 | 2.043653 | 1.431114 | -1.007270 | 0.722977 | -0.688205 | -1.332677 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 11.535787 | 11.535787 | 10.629806 | 1.034986 | 1.963192 | 1.216126 | 0.366545 | 0.615419 | -0.486848 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 12.030065 | 12.030065 | 11.647380 | 0.638365 | 0.654191 | 0.018064 | -0.359646 | -0.866460 | -0.508247 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 12.882267 | 12.150956 | 12.882267 | -0.030395 | 0.826070 | -0.828183 | -0.426194 | -0.347431 | -0.608988 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 8.839119 | 8.839119 | 7.231308 | 0.981154 | 0.659478 | -0.535560 | 0.123828 | 0.350581 | -0.388015 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 11.856045 | 10.504014 | 11.856045 | 0.864122 | 1.138214 | -0.241103 | -0.080198 | -0.563475 | -0.982278 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | ee Temporal Discontinuties | 86.636426 | 11.608880 | 9.781317 | 0.910668 | 0.013626 | -0.456988 | 8.287362 | -0.752886 | 86.636426 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | ee Temporal Discontinuties | 38.665378 | 13.221487 | 15.032129 | 0.359319 | 1.272964 | 9.637161 | 2.454155 | 38.665378 | 1.429280 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 9.503435 | 9.128897 | 9.503435 | 0.600020 | 1.143740 | -0.430413 | 0.403788 | 0.841596 | 0.390744 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | ee Shape | 11.016819 | 10.402937 | 11.016819 | 1.113647 | 0.901336 | 1.124988 | -0.038009 | 3.231141 | -0.493928 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 9.109864 | 9.109864 | 8.321450 | 0.978449 | -0.076577 | 0.913709 | -0.658873 | 2.278572 | -0.558162 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84 | N08 | digital_ok | nn Shape | 19.316557 | 19.316557 | 16.867172 | 0.772046 | -0.180092 | 1.887260 | -1.082286 | 0.446668 | 0.393953 |